CAREER: The Dynamics of Collective Intelligence

这个项目研究信息系统的设计，如维基和信息市场。社会科学的研究已经证实，通常存在一种“群体的智慧”--即，集体比组成集体的个人更有智慧。当这种集体信息系统发挥作用时，它们就成为信息的极好的汇集者和传播者。这项研究沿着几条路线推进，包括（1）关于信息如何在不同社交媒体中聚合的一般理论，使用从现有数据库收集的真实的数据和用户实验生成的数据进行开发和验证;（2）用于促进用户交互的算法，使得所讨论的介质可以提供所承诺的结果（例如，信息市场中提供流动性的做市算法）;（3）流氓用户操纵集体智慧系统的可能性的理论和实践特征;（4）检测恶意用户的算法，以及阻止恶意者的机制。这项研究自然是跨学科的，从机器学习和概率推理，数据挖掘和社交网络，以及金融和经济学。它有助于我们理解复杂的社会现象，如维基和博客中的信息增长，以及智能推理算法的发展，在复杂的，不确定的多智能体环境中，如市场。参与市场和社会系统的智能体的设计提高了在线市场的质量，并改善了虚拟空间中的信息流。此外，从建模市场结构和社会空间中获得的见解可以告诉我们如何更好地设计它们。例如，了解不同级别的中央控制对维基文章或开源软件项目的影响，就可以得出在不同环境下，中央控制的最佳程度的指导方针。在计算和社会系统日益交织在一起的世界中，PI的研究和教育计划通过引入一门关于集体智慧的新课程，社交网络和电子商务，以及在课堂和实验室环境中开发和广泛使用研究对象-信息市场和维基。PI还在开发一个实验项目，将免费访问的课程维基放在网上，类似于其他大学的在线课程材料，但开放给社区编辑。

This project studies the design of information systems like wikis and information markets. Research in social science has established that often there is a "wisdom of the crowd" -- i.e., collectives can display more intelligence than the individuals they are composed of. When such collective information systems work, they serve as superb aggregators and disseminators of information. However, fundamental computational challenges remain in understanding how to design them optimally.This research is advancing along several lines, including(1) general theories of how information is aggregated in different social media, developed and validated using real data gathered from existing databases and generated from user experiments; (2) algorithms for facilitation of user interactions so that the medium in question can deliver the promised results (for example, market-making algorithms for liquidity provision in information markets);(3) theoretical and practical characterization of the possibilities for rogue users to manipulate collective wisdom systems;(4) algorithms for detecting malicious users, and mechanisms that thwart miscreants. The research is naturally interdisciplinary in nature, drawing from machine learning and probabilistic reasoning, data mining and social networks, as well as finance and economics. It contributes to our understanding of complex social phenomena like the growth of information in wikis and blogs, as well as to the development of intelligent reasoning algorithms for agents in complex, uncertain multi-agent environments like markets.The design of agents that participate in markets and social systems improves the quality of online markets and improves information flow in virtual spaces. Further, insights gained from modeling market structures and social spaces can tell us how to design them better. For example, understanding the impact of different levels of central control on wiki articles or open source software projects yields guidelines for how much central control is optimal in different settings.In a world where computation and social systems are increasingly intertwined, the PI's research and education program exposes students to multidisciplinary ideas through the introduction of a new class on collective intelligence, social networks and e-commerce, and the development and extensive use of the very objects of study -- information markets and wikis -- in classroom and lab settings. The PI is also developing an experimental project for putting freely accessible course wikis online, similar to online course materials at other universities, but open to editing by the community.